Seventeen million people suffer from diarrhoeal disease in the UK annually. These diseases often lead to outbreaks of infections, like norovirus.

The sooner these outbreaks are detected the sooner they can be brought under control and their impact on health and the economy limited. Outbreaks of E. coli in the UK and Germany have shown that surveillance is the key to detection.

We will use data from multiple sources to scout for infection in the community, collect samples and analyse them, using modern technology to detect organisms. We will analyse the DNA of microbes to discover which family of organisms they belong to and how they are evolving.

Many causes of diarrhoea and vomiting can pass between humans and animals. However human and animal surveillance systems are poorly integrated, therefore it is difficult to identify where infection has passed between the two groups.

The challenge for this research programme is to modernise the approach to surveillance and clinical diagnosis by incorporating cutting edge research techniques and integrating veterinary and medical surveillance systems to create a one-health system.


  1. Shift from passive surveillance triggered when laboratories confirm an infection, to syndromic surveillance which uses health data in real-time or near real-time to manage people with symptoms and detect community outbreaks sooner
  2. Create a new, one-health model for detecting and investigating clusters and outbreaks of diarrhoea and vomiting in the community
  3. Enable Health Protection professionals and Environmental Health Officers to intervene quickly and so reduce short-and long-term harm


  • Adapt and calibrate an existing statistical model which analyses data in space and time and use the adapted model (AEGISS2) to analyse syndromic surveillance data to detect clusters of diarrhoeal disease in the community and produce maps of cases to be used by Health Protection professionals to identify outbreaks at an early stage (WP1)
  • Develop a one-health model by integrating veterinary syndromic surveillance data for domestic animals and livestock into the AEGISS2 model and calibrate these to help identify hotspots of gastrointestinal pathogens, the bugs that cause disease (WP1)
  • Use modern microbiology methods to target a wider range of pathogens and introduce a new method of discovering pathogens that cause gastrointestinal diseases based on next generation whole genome sequencing to identify new and possible emerging pathogens. (WP2)
  • Run the new system alongside the existing system to assess its performance, including the time from reporting to detection and whether or not a pathogen is identified (WP3)
  • Develop an economic model to assess the cost-effectiveness of active surveillance with public health management of patients with symptoms, compared to the current practice of passive surveillance (WP4)
  • Evaluate the implementation of the new surveillance system to determine the barriers to, and facilitators of, changing the surveillance system for diarrhoeal diseases from the perspective of service users and staff involved in implementing the new system (WP5)